Blockchain Market Research Report

Quantitative Analysis

1. Market Overview

Geographical Background

While blockchain technology itself is meant to be decentralised, constraints, such as the availability of talent, and whether cryptocurrencies are strongly or weakly regulated (for example, South Korea has banned initial coin offerings), may affect the distribution of blockchain companies across the world. Novum Insights has obtained country of domicile information for over 4400 companies, representing 75% of the total sample (those left blank were due to no location information being available in assessed sources or company websites being down during primary research). Figure 1 shows that activity within the blockchain ecosystem is dominated by companies in the United States, followed by mainland United Kingdom (excluding external territories such as Gibraltar and the British Virgin Islands), Singapore, Canada and Switzerland, along with the top 20 following countries by number of companies. Together, these top 20 countries represent >80% of the blockchain companies with location information tracked.

Figure 1: Number of companies tracked in each of the 20 most frequent countries of domicile.

When divided up by continent, the Americas and Europe dominate, with Asia (including the Middle East) having around half the activity of each of the two top regions, as shown in Figure 2.

Figure 2: Number of companies tracked in each region.

Investment statistics

Novum Insights has tracked approximately $15B in investment from 2009 to the present day for companies with available fundraising data. This includes information on size of investment, type of investment (e.g. series A), and dates of investment, as well as investor data where available. The data includes capital raised from initial coin offerings (ICOs) — both targeted at retail and institutional investors — as well as traditional venture capital rounds.

Investment in blockchain technologies, as shown in Figure 3, peaked at the end of 2017, in a manner that is qualitatively similar to the cryptocurrency boom and bust over the same period, but with a few months’ lag.

Figure 3: Total investment split by ICO/Venture in new companies as a function of time. Due to the prolonged nature of some funding rounds (e.g. ICOs accepting funds for over a year) amounts have been smoothed over the time period in question.

As Figure 3 highlights, ICOs dominate total investment, both by number of companies and amount raised. To date, over 70% of funds have been raised via this means, with ICOs constituting 74% of all recorded investments in blockchain. However, as Figure 4 shows, ICOs experience a high variance in the amount raised compared to traditional venture rounds. In this sense, they can be seen to act as substitutes for at least Series A and B in the traditional startup investment pipeline, given the similarity in the distributions of raised amounts being focused around $1M — $10M, though in many cases they have also competed against much more mature investment stages, with several ICOs raising capital in the tens to hundreds of millions (and in some cases billions). However, the blockchain ecosystem is not yet mature enough to produce a significant amount of late-stage investment in this space and some early evidence suggests that a growing number of blockchain companies are moving back towards venture funding or tightly-controlled private ICOs for growth investment. Indeed, there may be a good case for developing a framework to further subdivide ICOs by this criteria. Having said that, the data also suggests that bootstrapping, seed funding and angel investing are still necessary while companies build a prototype and develop a concept far enough to take it to the token market.

However, whilst some rounds (and in particular ICOs) have raised astronomical amounts over the last year, this distribution is highly skewed towards a small number of extremely large raises. Indeed, the total raised amount is becoming dominated by a small number of large ICOs, with the top 5% of companies raising over 55% of the total amount for rounds with recorded raised amounts. The median amount raised was $1.5M, with the 25% and 75% quartiles being $300K and $8.5M respectively. Yet the distribution is not log-normal, having a notable negative skew (-1.9). The largest capital raisings are described in Table 1. Together, companies in this table account for approximately 25% of all tracked fundraising.

Figure 5: shows the cumulative distribution of raised amounts as a ECDF (Empirical Cumulative Distribution Function) of total percentage, highlighting the significant skew of investment sizes.

Company

End Date

Description

Amount raised ($M, USD)

EOS

2018-06-01

Cryptocurrency protocol with smart contracts

1100

Telegram

2018-03-29

Private messaging application

850

Bitmain

2018-06-11

Cryptocurrency mining hardware manufacturer

400

Robinhood

2018-03-15

Financial trading platform (crypto, equities)

360

Dragon

2018-03-15

Cryptocurrency casino and gambling platform

320

Filecoin

2017-09-10

Decentralised file storage platform

260

Tezos

2017-07-13

Cryptocurrency protocol

230

Circle

2018-05-15

Peer to peer payments (fiat and cryptocurrency)

246

Sirin Labs

2017-12-26

Consumer electronics

158

Bancor Protocol

2017-06-01

Cryptocurrency liquidity exchange protocol

150

Table 1: Capital raises over $150M.

2. Sector / Application Breakdown

Of the 5800 companies tracked, 100% have at least one sector tag and at least one application tag. Companies were allotted up to five tags per sector and per application, with the first tag representing the ‘primary’ or main sector/application of that company and the second representing a ‘secondary’ tag if applicable, et cetera. Over 80% had data on the blockchain protocol technology used, with the missing 20% due to a lack of data available online during primary research into which protocol (if any) a company was using for their blockchain layer.

Figure 7: The number of companies with a given primary sector tag.

Figure 7 shows the number of companies with a given primary sector tag. Financial applications dominate both in terms of number of companies and funds raised, with the blockchain ecosystem in third place. Non-financial, and non-blockchain technologies have comparatively few companies with the exception of IT/Analytics (mostly in the field of decentralised computing, storage, and AI).

Figure 8: The number of companies with a given primary tag as a function of the date at which the corresponding investment concludes.

Figure 8 shows how this distribution of sectors evolves over time. There is a clear run-up of interest in the two financial sectors and blockchain technology, with a marked increase in the rate at which new companies incorporate and seek to raise funds starting around Q2-Q3 2017. This rate is correlated with both the Bitcoin price (with a couple of months’ delay) and Google Trends data on Bitcoin, cryptocurrencies and blockchain (3), suggesting a hype-driven development cycle similar to the dot com era as entrepreneurs and investors seek to find use-cases based on maturing blockchain technology systems. Indeed, it is no coincidence that financial services, financial exchanges and financial funding platforms are the mostly rapidly growing sectors, as well as being the most prominent and obvious uses of blockchain technology (as blockchain’s debut application was the Bitcoin cryptocurrency and payment system).

In comparison, new start-up activity and funding for core blockchain technologies and base protocols show early signs of dropping off into 2018, as a smaller number of large players with significant capital are backing mature companies and are attempting to monopolise the protocol layer space. Indeed, as Figure 9 shows, blockchain ecosystem startups were one of the only sectors (4) to see a relative drop in the number of new companies and investment from 2017 to 2018 (to date (5).

Figure 9: The difference between the number of new investment rounds ending in 2017 versus 2018 (to date) based of funding round end date.

This finding holds true, and is in fact more marked, when looking at both the amount raised for new blockchain ecosystem rounds (based on start date of a round), as well as the percentage difference of number of new rounds (compared to absolute difference as above), suggesting that the slowing down and maturing of blockchain protocol and core technologies is a genuine, observable trend.

Figure 10: Number of companies versus total raised amount for each primary sector.

Figures 9 and 10 give an insight into the maturity of the various sectors. Blockchain ecosystem companies (building fundamental protocol layer solutions), for example, show clear signs of maturing, with the growth rate of the number of new companies slowing down (Figure 9), while a fewer number of large players continue to raise large amounts of capital in an attempt to monopolise the technology infrastructure on which blockchain use-cases can be built (Figure 10). This is indicated by the average amount raised per company in this space increasing (while the number of new contenders fall), as companies reach later stages in the successful startup lifecycle.

The two financial sectors, on the other hand, rank highest in amount raised, number of companies, and growth rate, indicating large amounts of entrepreneurial activity and many high-value contenders. Due to this clear cluster of activity in financial use-cases, it could be conjectured that financial solutions represent a form of ‘first wave’ blockchain use-cases. Indeed, the financial sector has moved beyond initial exploration of blockchain solutions and has demonstrated clear and increasing momentum, both in terms of investor interest and the number of new contenders. However, given the number of players with similar value propositions (e.g. generalised cryptocurrency exchange platforms and payment systems) and the relative maturity of some solutions in this space, it is unlikely that all of these companies in the financial sectors will survive in the long run, with a general trend towards monopolisation by a few successful players.

Finally, under this framework, a ‘second wave’ of non-financial sector use-cases can also be identified from Figure 10, with a much smaller number of companies and investment sizes attempting to find valuable use-cases for blockchain outside of the financial realm. This cluster can be summarised as having a relatively fewer number of contending companies, as well as smaller current investment sizes, though with high and increasing growth rates over time. Under this lens, it is likely that at least some of these non-financial sectors will follow a similar growth trajectory to financial applications, with increasing investor interest and contenders competing to own the space, as well as IT/Analytics (especially for decentralised computing, storage, and AI) already showing some signs of following this pattern. Having said that, the blockchain market for these sectors is still incredibly young and some of these sectors may not find any natural (and high value) use-cases for blockchain within their domain. Indeed, as increasing number of companies in these spaces fail to monetise and prove value, this could lead to still-starts and declines in other sectors, potentially leading to a further split within this second wave. However, more information is needed before any firm conclusions are drawn here.

Figure 11: Number of companies as a function of investment round end date for all sectors excluding finance and blockchain ecosystem. (This is a subset of Figure 8.)

As discussed, the deployment of blockchain technologies in non-financial sectors remains immature, both in terms of total companies (Figure 7) and amounts raised (Figure 8 and bottom left corner of Figure 10). These sectors are generally steadily growing (Figure 9). This suggests that while the hype cycle is fading away, exploration of how blockchain can be used to solve non-financial problems is slowly picking up pace. Figure 11 zooms in on the non-financial sectors in Figure 8. IT/Analytics (with emphasis on decentralised computing, storage, AI and Big Data use-cases) is a front-runner, showing both large growth in funding and a large number of companies in a manner that rivals financial services (Figure 9). This is followed by Retail and Consumer Products (peer to peer (P2P) marketplaces and loyalty rewards), then by Energy and Power. It is likely that these represent a second wave in the application of blockchain technology, perhaps in order of obviousness, barriers to entry and the potential gains a blockchain-powered application might bring over existing solutions.

Figure 12: Number of companies versus total amount raised for non-financial and non-blockchain sectors, logged to emphasis scale difference.

Indeed, Figure 12 shows that there is a distribution in this second wave from the relatively mature sectors (IT/Analytics) to the very immature (Manufacturing and Mobility). Clearly there is still potential for high-value opportunities in the sectors that are the least mature. It should be noted here, however, that this view of sectoral splits is somewhat distorted by the short-tail of very large ICO investments in some of these areas. For example, Social Media is significantly distorted by the presence of the recent Telegram ICO ($850M). If reanalysed without Telegram, this sector is indistinguishable from the remainder.

Figure 13: Number of companies with the given primary application tag.

Figure 13 shows the breakdown of primary application tags. Given that the majority of investment in blockchain companies relates to financial services and the blockchain ecosystem, it is unsurprising to see applications being dominated by marketplaces, payment systems and money management tools. This is a result of blockchain’s debut use as a distributed payment system and the infamous Silk Road marketplace. Data and information sharing comes in third place, as blockchain’s properties as a distributed, immutable record are favourable to this application. Likewise, Digitisation of Assets and Digital Identity have relatively more applications. Other applications are in the early stages of development.

Figure 14: Number of companies primarily using an identified blockchain protocol technology, as a function of time.

Finally, Figure 14 shows the total number of companies using a particular blockchain technology over time. The blockchain ecosystem is, for the most part, dominated by Ethereum, with over 1600 companies identified built primarily on the Ethereum MainNet. Considering that Ethereum is the pioneer of scripting on the blockchain and has first mover advantage in a field where there are network effects, this is to be expected. As the first mover, Ethereum has established tooling that makes it easier to develop distributed apps (dapps) and partially automates the task of conducting ICOs and setting up complex blockchain ecosystems through smart contracts. This supports the hypothesis of an emerging wave of distributed apps for the resolution of real-world problems, built on maturing fundamental infrastructure projects like Ethereum. However, it should be noted that Figure 14 excludes the ‘Other’ category for this field, which means the technology has been built on a bespoke protocol or the company has announced a so-called ‘token swap’ to transition over from a generic protocol like Ethereum to their own blockchain. Indeed, this category, if included, would be almost comparable in size to that of Ethereum protocols, suggesting that — while Ethereum currently dominates the generic protocol space — it may increasingly face competition from a heterogenous group of bespoke and tailored systems. It would be interesting to revisit this question when technically superior scripting platforms suitable to specific real-world problems become mature in a few years’ time. Indeed, the protocol question is further complexified by the increasing number of companies within the blockchain space offering interoperability between blockchains (e.g. Wanchain), potentially making the notion of a single, primary blockchain per company less salient in the future anyway.

Finally, it is also worth mentioning that Figure 14 above excludes the ‘None’ category, which represents some 1000 companies emerging to service the blockchain market, without directly using blockchain technologies. For example, the growth of blockchain consulting and legal services, which come under this category, have exploded in the wake of the hype-cycle and billion dollar investment activities around this market.

3. Cross-Correlation

Cross-correlation analysis of sector and application tags gives a high-level view of the blockchain ecosystem and helps to further segment the market. For instance, it yields evidence that a given space is crowded and suggests places to look for potentially interesting early investment opportunities. In a relatively underpopulated space, this analysis allows the user to drill down to specific companies. For example, Figure 15 shows a cross-section correlation heatmap of application versus sector. This analysis uses all five application and sector tags when specified. The sectors identified as relevant to Hitachi are highlighted.

Figure 15: Cross-correlation of sector and application tags. The number in each cell shows the number of companies that are tagged with the corresponding sector and application tags. The companies are ordered from top to bottom in terms of indicated interest for Hitachi.

The cross-correlation shows a number of intersections where there are very few companies. However, only qualitative analysis can separate intersections that are potentially interesting versus those that are nonsensical (for example, as discussed in the methodology, some sectors/applications such as “Gambling/Prediction Markets” and “Corporate Governance” may have zero companies because there is no obvious business-value overlap between these areas, or because there are crossover areas that are either without merit or are otherwise unfit for purpose). Despite some sectors being very crowded, there are still potential investment opportunities in underpopulated niches — for example, trade finance (“Financial Services” and “Supply Chain”) or back-office operations (“Funding, Investment and Trading” and “Corporate Governance” or “Regulatory, Compliance and Audits”). A closer, qualitative examination of the companies in that niche is needed to determine the action that Hitachi should take. This analysis is conducted in the second part of this report.

Figure 16: Cross-correlation of sector tags for companies with at least two sector tags. Companies are ordered from top to bottom and left to right in terms of indicated interest to Hitachi. It should be noted that all self-correlations (e.g. same sector diagonals) have been replaced by a ‘-1’ code to make genuine correlations more visible.

Likewise, Figure 16 shows the same analysis, but for the first sector tag versus every other sector tag. Again, the sectors identified as being relevant to Hitachi are to the top left of the chart above the greyed-out box. An intersection of sectors may indicate one of two things — firstly, a blockchain solution that may be tailored to a specific industry, such as a company that offers P2P student lending being classified as both “Education and academia” and “Financial services”. The second case is where solutions impact many sectors, for example, a generalised inventory management system (such a system may be marketed within the “Healthcare”, “Manufacturing” and “Retail and Consumer Products” sectors). Again, this stresses the need for follow-up qualitative analysis.

It is clear that there is relatively little investment in horizontal or tailored solutions. Horizontal solutions are particularly interesting to Hitachi given their nature as a manufacturing-focused conglomerate and could prove lucrative, as the same solution can improve many aspects of Hitachi’s business.

Figure 17: Cross-correlation of application tags for companies with at least two application tags. Again, same application correlation diagonals have been replaced with a ‘-1’ code to aid visibility.

Finally, Figure 17 shows the same analysis but for the first application tag versus every other application tag. Again, the most frequently appearing solutions involve payments and decentralised markets due to the history of blockchain technology. As with sector correlations, an intersection may indicate a specific solution (a marketplace for trading personal travel data for goods, services and/or cryptocurrencies would be “Data Sharing” and “Marketplace”) or a blockchain software package that has multiple purposes (a new cryptocurrency provably backed by gold is a “digitised asset”, a “marketplace” and a “payment system”, due to gold’s status as a store of value). Intersections outside the obvious and most frequent applications also show signs of relative underinvestment and could present early investment opportunities. Blockchain platforms with multiple purposes are of particular interest to Hitachi given their business model as a multinational conglomerate.

4. Conclusions

This analysis asserts that there is a clear distinction emerging between blockchain core systems, a first wave of financial applications, and a second wave of non-financial solutions. The number of new blockchain core companies is slowing down and current technologies are maturing, though it is still unclear if the current protocols are fit for all purposes. Financial applications are currently exploding both in terms of new companies and investment raised, though gaps remain for financial applications in niche industries. All three sectors show signs of a hype-driven development cycle. It is highly uncertain which companies will survive.

A whole host of non-financial applications are just recently emerging. This second wave is differentiated in maturity, with the front-runners being applications of blockchain technology to the IT and energy industries and some others, such as manufacturing, lagging behind. It is still unclear which of these will face insurmountable barriers to entry and which will have real success. However, some of these barriers to entry are easy for Hitachi, as a large, established, diversified multinational company, to overcome.

The quantitative analysis allows an analyst to isolate potential blockchain powered solutions for further analysis. However, a qualitative analysis is needed to drill down into each white space and determine whether the white space is logical, whether the application of blockchain results in an improvement over existing solutions, whether blockchain is the best solution for any given problem and, finally, whether an investment opportunity exists.